Home AI News Hybrid Learning for Wearable Cardiovascular Biomarker Monitoring at NeurIPS 2023

Hybrid Learning for Wearable Cardiovascular Biomarker Monitoring at NeurIPS 2023

0
Hybrid Learning for Wearable Cardiovascular Biomarker Monitoring at NeurIPS 2023

NeurIPS 2023 Workshop Acceptance

A paper has been accepted at the workshop Deep Generative Models for Health at NeurIPS 2023. The workshop is a major gathering for researchers and experts in the field of artificial intelligence and health.

Significance of Monitoring Cardiovascular Biomarkers

Cardiovascular diseases (CVDs) are a significant concern for global health. Monitoring cardiovascular biomarkers over time is crucial for early diagnosis and intervention. However, traditionally, it has been challenging to infer cardiac pulse parameters from pulse waves, especially when using wearable sensors at peripheral body locations. This is because of a lack of labeled data and the complexity of physical models.

A Novel Hybrid Learning Approach

This paper presents a novel hybrid learning approach to address these challenges. By combining a pulse-wave propagation simulator with a data-driven correction model, the methodology aims to blend the rigor of physical models with the flexibility of ML. This offers a promising avenue for effective cardiovascular biomarker monitoring that could revolutionize the way we approach cardiovascular health.

Source link

LEAVE A REPLY

Please enter your comment!
Please enter your name here